Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 90 681 238 116 548 505 653 39 134 637 170 374 369 957 240 356 839 96 60 111
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] NA NA 134 505 NA 39 240 96 90 111 957 839 116 170 356 60 238 681 369 653 374 548 637
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 3 5 1 5 3 5 1 5 1 5
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "j" "v" "l" "i" "m" "Z" "S" "A" "N" "C"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 14
which( manyNumbersWithNA > 900 )
[1] 11
which( is.na( manyNumbersWithNA ) )
[1] 1 2 5
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 957
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 957
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 957
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "Z" "S" "A" "N" "C"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "j" "v" "l" "i" "m"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE TRUE FALSE FALSE
[19] FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 5 6 12 13 16
sum( manyNumbers %in% 300:600 )
[1] 5
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] NA NA "small" "large" NA "small" "small" "small" "small" "small" "large" "large" "small" "small"
[15] "small" "small" "small" "large" "small" "large" "small" "large" "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "UNKNOWN" "UNKNOWN" "small" "large" "UNKNOWN" "small" "small" "small" "small" "small" "large"
[12] "large" "small" "small" "small" "small" "small" "large" "small" "large" "small" "large"
[23] "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] NA NA 0 505 NA 0 0 0 0 0 957 839 0 0 0 0 0 681 0 653 0 548 637
unique( duplicatedNumbers )
[1] 3 5 1
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 3 5 1
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 11
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 957
which.min( manyNumbersWithNA )
[1] 6
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 39
range( manyNumbersWithNA, na.rm = TRUE )
[1] 39 957
manyNumbersWithNA
[1] NA NA 134 505 NA 39 240 96 90 111 957 839 116 170 356 60 238 681 369 653 374 548 637
sort( manyNumbersWithNA )
[1] 39 60 90 96 111 116 134 170 238 240 356 369 374 505 548 637 653 681 839 957
sort( manyNumbersWithNA, na.last = TRUE )
[1] 39 60 90 96 111 116 134 170 238 240 356 369 374 505 548 637 653 681 839 957 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 957 839 681 653 637 548 505 374 369 356 240 238 170 134 116 111 96 90 60 39 NA NA NA
manyNumbersWithNA[1:5]
[1] NA NA 134 505 NA
order( manyNumbersWithNA[1:5] )
[1] 3 4 1 2 5
rank( manyNumbersWithNA[1:5] )
[1] 3 4 1 2 5
sort( mixedLetters )
[1] "A" "C" "i" "j" "l" "m" "N" "S" "v" "Z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 2.0 5.5 8.5 2.0 7.0 8.5 5.5 10.0 4.0 2.0
rank( manyDuplicates, ties.method = "min" )
[1] 1 5 8 1 7 8 5 10 4 1
rank( manyDuplicates, ties.method = "random" )
[1] 3 5 8 2 7 9 6 10 4 1
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.000000000 -0.500000000 0.000000000 0.500000000 1.000000000 1.457656334 -1.505883670 1.085477051
[9] -0.738247661 1.631141894 0.495322502 -0.033199100 -0.870309233 -0.007816511 1.413983911
round( v, 0 )
[1] -1 0 0 0 1 1 -2 1 -1 2 0 0 -1 0 1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 1.5 -1.5 1.1 -0.7 1.6 0.5 0.0 -0.9 0.0 1.4
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 1.46 -1.51 1.09 -0.74 1.63 0.50 -0.03 -0.87 -0.01 1.41
floor( v )
[1] -1 -1 0 0 1 1 -2 1 -1 1 0 -1 -1 -1 1
ceiling( v )
[1] -1 0 0 1 1 2 -1 2 0 2 1 0 0 0 2
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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